ADVANCED TOPICS IN STATISTICS E

STA4ATE

2020

Credit points: 15

Subject outline

This subject enables 4th year statistics students to enrol in subjects offered through the Key Centre of Statistical Science (KCSS) or through the Department of Mathematics and Statistics Access Grid Room. Subject syllabus is dependent on the subject chosen and students are advised to refer to the departmental website or the Department of Mathematics and Statistics Honours Coordinator prior to enrolment for more details. Enrolment into this subject must be approved by the Department of Mathematics and Statistics Honours Coordinator.

School: Engineering and Mathematical Sciences (Pre 2022)

Credit points: 15

Subject Co-ordinator: Tomasz Kowalski

Available to Study Abroad/Exchange Students: Yes

Subject year level: Year Level 4 - UG/Hons/1st Yr PG

Exchange Students: No

Available as Elective: No

Learning Activities: N/A

Capstone subject: No

Subject particulars

Subject rules

Prerequisites: Students must have been accepted into the Department of Mathematics and Statistics Honours program

Co-requisites: N/A

Incompatible subjects: STA5ATE

Equivalent subjects: N/A

Quota Management Strategy: N/A

Quota-conditions or rules: N/A

Special conditions: N/A

Minimum credit point requirement: N/A

Assumed knowledge: N/A

Career Ready

Career-focused: No

Work-based learning: No

Self sourced or Uni sourced: N/A

Entire subject or partial subject: N/A

Total hours/days required: N/A

Location of WBL activity (region): N/A

WBL addtional requirements: N/A

Graduate capabilities & intended learning outcomes

Graduate Capabilities

Intended Learning Outcomes

01. Demonstrate advanced theoretical and technical knowledge in a specified statistics topic.

02. Use advanced cognitive and technical skills to select and apply methods to critically analyse, evaluate and interpret tasks relevant to the topic.

03. Use advanced cognitive and technical skills to analyse, generate and transmit solutions to complex problems relevant to the topic.

04. Use advanced communication skills to transmit knowledge and ideas of statistics to others.

05. Demonstrate autonomy, well-developed judgement, adaptability and responsibility as a statistician.

Melbourne (Bundoora), 2020, Semester 1, Day

Overview

Online enrolment: No

Maximum enrolment size: N/A

Enrolment information: N/A

Subject Instance Co-ordinator: Tomasz Kowalski

Class requirements

LectureWeek: 10 - 22
One 2.00 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
This is dependent on the subject chosen though subject typically consist of two contact hours per week.

Assessments

Assessment element	Comments	Category	Contribution	Hurdle	%	ILO*
This is dependent on the subject.	N/A	N/A	N/A	No	100	SILO1, SILO2, SILO3, SILO4, SILO5

Melbourne (Bundoora), 2020, Semester 2, Day